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Exports and cross-national corruption: A disaggregated examination

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  • Goel, Rajeev K.
  • Korhonen, Iikka

Abstract

This paper empirically examines the relation between categories of exports and corruption across countries. Aggregate exports and agricultural exports tend to decrease corruption, while fuel exports increase corruption. The influence of agricultural exports in more pronounced in more corrupt nations, while fuel exports contribute to corruption in least corrupt nations. Manufacturing and ore exports, on the other hand, generally fail to show significant impacts on corruption. Our findings demonstrate that the resource curse is sensitive to prevailing corruption levels, and this finding is novel in the literature. Consistent with the extant literature, corruption decreases with income, and (at some corruption levels) as political freedom increases, and with larger government size. The findings are fairly robust to an alternate corruption measure.

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  • Goel, Rajeev K. & Korhonen, Iikka, 2011. "Exports and cross-national corruption: A disaggregated examination," Economic Systems, Elsevier, vol. 35(1), pages 109-124, March.
    • Handle: RePEc:eee:ecosys:v:35:y:2011:i:1:p:109-124
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    2. Marc Audi & Amjad Ali, 2019. "Exploring the Linkage between Corruption and Economic Development in The Case of Selected Developing and Developed Nations," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 37-49.
    3. Faruq, Hasan A., 2011. "How institutions affect export quality," Economic Systems, Elsevier, vol. 35(4), pages 586-606.
    4. Yuanyuan Zhu & Xiaoqi Zhou & Yilin Gan & Jing Chen & Ruilin Yu, 2021. "Spatio-Temporal Differentiation and Driving Mechanism of the “Resource Curse” of the Cultivated Land in Main Agricultural Production Regions: A Case Study of Jianghan Plain, Central China," IJERPH, MDPI, vol. 18(3), pages 1-17, January.
    5. Ferreira, João J. & Gomes, Sofia & Lopes, João M. & Zhang, Justin Z., 2023. "Ticking time bombs: The MENA and SSA regions' geopolitical risks," Resources Policy, Elsevier, vol. 85(PA).
    6. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    7. repec:hhs:bofitp:2011_031 is not listed on IDEAS
    8. Veronika Belousova & Rajeev Goel & Iikka Korhonen, 2016. "Corruption perceptions versus corruption incidence: Competition for rents across Russian regions," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 172-187, January.
    9. You, Jing & Nie, Huihua, 2017. "Who determines Chinese firms' engagement in corruption: Themselves or neighbors?," China Economic Review, Elsevier, vol. 43(C), pages 29-46.
    10. Belousova, Veronika & Rajeev, K. Goel & Korhonen, Iikka, 2011. "Causes of Corruption in Russia: A Disaggregated Analysis," Discussion Paper Series 557, Institute of Economic Research, Hitotsubashi University.

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    More about this item

    Keywords

    Corruption Exports Resource curse Government Quantile regression;

    JEL classification:

    • H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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